Radar—Create Awesome Portfolio Projects To Land Your Dream Job

his unexpected move into growth engineering. By aligning personal interests with professional skills, candidates can create projects that not only showcase their technical abilities but also their unique personalities. "One really good portfolio project can help you discover your own passion," Nick notes, emphasizing the dual benefit of personal satisfaction and professional advancement.

Avoiding Common Mistakes

One of the most common errors in portfolio projects is failing to make them interesting. Nick advises against using repetitive datasets, such as those available on Kaggle, and instead advocates the use of unique and visually appealing data. The story behind the project is equally important, as it allows candidates to connect with interviewers on a personal level. It's not only about the data; it's also about the narrative that links personal passion with professional skills. As Nick puts it, "There's an art to being interesting," and mastering this art can set a candidate apart from others.

Completing and Sharing Projects

The saying "done is better than perfect" is central to Nick's advice. A finished project with a clickable link is far more valuable than an unfinished masterpiece. He emphasizes the importance of making projects accessible, whether through a personal website, GitHub, or platforms like Tableau Public. This accessibility not only shows technical competence but also a commitment to sharing work with the wider community. Nick suggests, "Even when we're face to face and I can't click on the link, having a link goes such a long way," highlighting the importance of visibility in project presentation.

Using Unique Datasets

Nick encourages data enthusiasts to go beyond standard datasets and explore more unique, niche opportunities. He suggests scraping data from various sources or even using personal data from services like Amazon or Tinder. By dealing with real-world data complexities, candidates can demonstrate their problem-solving skills and readiness for industry challenges. This approach not only showcases technical skills but also creativity in data selection and analysis. "There's just so much out there," Nick remarks, urging aspiring data scientists to be proactive and innovative in their data exploration efforts.